code: def test_flip_sub_unique(self):
      for dtype in (torch.float, torch.double):
          tkwargs = {"device": self.device, "dtype": dtype}
          x = torch.tensor(
              [0.69, 0.75, 0.69, 0.21, 0.86, 0.21], **tkwargs
          )
          y = _flip_sub_unique(x=x, k=1)
          y_exp = torch.tensor([0.21], **tkwargs)
          self.assertAllClose(y, y_exp)
          y = _flip_sub_unique(x=x, k=3)
          y_exp = torch.tensor([0.21, 0.86, 0.69], **tkwargs)
          self.assertAllClose(y, y_exp)
          y = _flip_sub_unique(x=x, k=10)
          y_exp = torch.tensor([0.21, 0.86, 0.69, 0.75], **tkwargs)
          self.assertAllClose(y, y_exp)
      # long dtype
      tkwargs["dtype"] = torch.long
      x = torch.tensor([1, 6, 4, 3, 6, 3], **tkwargs)
      y = _flip_sub_unique(x=x, k=1)
      y_exp = torch.tensor([3], **tkwargs)
      self.assertAllClose(y, y_exp)
      y = _flip_sub_unique(x=x, k=3)
      y_exp = torch.tensor([3, 6, 4], **tkwargs)
      self.assertAllClose(y, y_exp)
      y = _flip_sub_unique(x=x, k=4)
      y_exp = torch.tensor([3, 6, 4, 1], **tkwargs)
      self.assertAllClose(y, y_exp)
      y = _flip_sub_unique(x=x, k=10)
      self.assertAllClose(y, y_exp)
  
file_path: botorch/test/generation/test_utils.py
imports: from __future__ import annotations
  from itertools import product
  import torch
  from botorch.acquisition import FixedFeatureAcquisitionFunction
  from botorch.generation.utils import _convert_nonlinear_inequality_constraints, _flip_sub_unique, _remove_fixed_features_from_optimization
  from botorch.utils.testing import BotorchTestCase, MockAcquisitionFunction
label_desc: Use image node_id 2 for calling the TestGenerationUtils obj's underlying member method code with example usage: obj.test_flip_sub_unique() without return types